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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "dagHMM" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'dagHMM: Directed Acyclic Graph HMM with TAN Structured Emissions'
version: 0.1.1
doi: 10.32614/CRAN.package.dagHMM
abstract: Hidden Markov models (HMMs) are a formal foundation for making probabilistic
  models of linear sequence. They provide a conceptual toolkit for building complex
  models just by drawing an intuitive picture. They are at the heart of a diverse
  range of programs, including genefinding, profile searches, multiple sequence alignment
  and regulatory site identification. HMMs are the Legos of computational sequence
  analysis. In graph theory, a tree is an undirected graph in which any two vertices
  are connected by exactly one path, or equivalently a connected acyclic undirected
  graph. Tree represents the nodes connected by edges. It is a non-linear data structure.
  A poly-tree is simply a directed acyclic graph whose underlying undirected graph
  is a tree. The model proposed in this package is the same as an HMM but where the
  states are linked via a polytree structure rather than a simple path.
authors:
- family-names: Bende
  given-names: Prajwal
  email: prajwal.bende@gmail.com
repository: https://mrprajwalb.r-universe.dev
commit: 766fa8dcbf51755460bfd3645d95b1f9883c0e10
date-released: '2025-07-18'
contact:
- family-names: Bende
  given-names: Prajwal
  email: prajwal.bende@gmail.com